I wrote the book on when AI deployments fail.
"Hire me so yours doesn't."
Independent AI risk assessment and governance consulting for small professional firms, rooted in a documented six-risk framework and hands-on evaluation of frontier models.
The Six-Risk Framework
The methodology behind the book, a systematic lens for evaluating AI deployments before and after they go live. Every engagement is run against these six categories. No proprietary black box; you see exactly where the risks land and what to do about them.
Data & Confidentiality
What client data enters the model, where it goes, and who can see it downstream. The Samsung leak was this category.
Output Reliability
Hallucination rates, citation fabrication, and what "close enough" actually costs in a professional context.
Verification Tax
The hidden time cost of checking AI output. Whether the "hour saved" is real or a liability in disguise.
Liability Exposure
Who signs off on AI-assisted work and what professional liability rules apply when it goes wrong.
Vendor Accountability
What the terms of service actually say and what recourse you have when the tool changes, fails, or disappears.
Scope Creep
How a narrowly-scoped pilot expands into unsupervised use across the firm, and how to prevent it structurally.
One engagement. Five deliverables.
The starter package is designed for small professional firms (solo to ten-person practices) already using AI or actively evaluating it. Fixed fee. Concrete outputs. No retainer required to start.
AI Risk Assessment
- → AI-use inventory of the firm
- → Risk memo against the six categories
- → Written AI usage policy
- → Vendor due-diligence assessment
- → One staff training session
Pre-Adoption Diligence
- → Evaluation of a specific tool or platform
- → Four-move memo for leadership
- → Scoped-use policy for the application
- → Incident log template
- → Cost-benefit worksheet
Ongoing Governance
- → Full governance framework design
- → ISO 42001 gap assessment
- → Regulatory readiness review
- → Quarterly risk update memos
- → Staff training, multi-session
The stakes are higher when you bill by the hour.
Small law firms face AI risks that differ in kind from corporate deployments. Confidentiality rules don't bend. Professional liability follows the attorney who signed off. And the tools being adopted were not built with your obligations in mind.
Chapter 14 of the book maps ABA Opinion 512 and the Model Rules directly to AI use in legal practice. The consulting engagements apply that research to your specific firm.
Estate attorneys, title companies, and solo practitioners are adopting AI tools at pace, often without a compliance officer, a technology committee, or any process for evaluating what they're putting client data into.
The same diligence the book teaches employees to demand can be commissioned from the top. Same framework. Different table. You get an independent assessment with no vendor stake in the outcome.
The credential is the work.
The consulting practice is built on documented research, not theory. When AI Is Wrong for the Job is a systematic analysis of real AI deployment failures, mapped against a repeatable risk framework and written for leaders, builders, and decision-makers who need to act on what they find.
That research is what gets applied to your firm. Conservative estimates. Honest citations. No overclaiming. The same credibility standard the book holds itself to.
Engineers pasted proprietary source code into ChatGPT. Immediate confidentiality breach with no recovery mechanism and no contractual recourse.
Chatbot gave a customer incorrect bereavement fare policy. Tribunal held Air Canada liable for its AI's statements regardless of disclaimers.
AI-assisted compliance tools missed flagged entities. Liability fell on the firm that relied on the output without independent verification.
AI screening tools introduced discriminatory bias in hiring decisions. EEOC scrutiny and litigation exposure followed the employer, not the vendor.
Applied research for practitioners.
Ongoing articles applying the book's framework to specific professional contexts, published here and on LinkedIn. Written for the firms this work is designed to serve.
What happens when your paralegal pastes a client's trust into ChatGPT
A step-by-step breakdown of the data flow, the confidentiality exposure, and what Rule 1.6 actually requires of supervising attorneys.
The sanctions wave and why it lands on whoever signs
How AI-assisted compliance tools are failing at the margins, and the enforcement pattern that's emerging around them.
ABA Opinion 512 in plain English for small firms
What the opinion actually says about competence, supervision, and confidentiality, and what a three-person estate practice should do about it.
How to vet an AI vendor when you're a three-person firm
The due-diligence checklist from the book's appendix applied to a real vendor evaluation: what questions to ask and what answers to reject.
The verification tax: what the "hour saved" really costs a billing practice
Breaking down the hidden time cost of reviewing AI output, and the math that changes the ROI calculation for attorneys.
An AI usage policy for a solo estate practice
A worked example of the scoped-use template from the appendix, adapted for a solo practitioner with two paralegals using three AI tools.
Find out where your firm's AI exposure actually is.
Fixed-fee engagement. No retainer.
No vendor stake in the recommendation.